论文标题

COVID-19和扁平曲线:反馈控制视角

Covid-19 and Flattening the Curve: a Feedback Control Perspective

论文作者

Di Lauro, Francesco, Kiss, István Z., Rus, Daniela, Della Santina, Cosimo

论文摘要

在199年大流行期间制定的许多控制政策都有一个共同的目标:使受感染者数量的曲线扁平,以使其峰保持在临界阈值之下。这封信考虑了工程的挑战,一种使用控制理论实施此类目标的策略。我们介绍了最佳扁平问题的简单公式,并提供了封闭式解决方案。通过标称解决方案的非线性闭环跟踪,这将增强,目的是确保在不确定条件下近距离性能。本文的一个关键贡献是在Covid -19场景中通过广泛而逼真的模拟来验证该方法,特别关注Codogno的案例 - 科德诺(Codogno)是意大利北部的一个小城市,一直受到大流行最严重的打击。

Many of the control policies that were put into place during the Covid-19 pandemic had a common goal: to flatten the curve of the number of infected people so that its peak remains under a critical threshold. This letter considers the challenge of engineering a strategy that enforces such a goal using control theory. We introduce a simple formulation of the optimal flattening problem, and provide a closed form solution.This is augmented through nonlinear closed loop tracking of the nominal solution, with the aim of ensuring close-to-optimal performance under uncertain conditions. A key contribution ofthis paper is to provide validation of the method with extensive and realistic simulations in a Covid-19 scenario, with particular focus on the case of Codogno - a small city in Northern Italy that has been among the most harshly hit by the pandemic.

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